• Design and build scalable search and retrieval systems combining lexical and semantic approaches. • Develop and maintain connectors to enterprise data sources (SaaS platforms, data warehouses, document stores, APIs). • Build data pipelines that ingest, transform, and index customer data for use by AI agents. • Integrate with LLM providers and related frameworks (e.g., LangChain, LlamaIndex) to deliver context-aware agent capabilities. • Pull and process analytics data from customers' warehouses (Snowflake, BigQuery, Databricks, etc.). • Own projects end-to-end: from architecture and technical design through implementation, deployment, and ongoing maintenance. • Collaborate with product and AI teams to translate retrieval quality into measurable agent performance improvements. • Optimize retrieval pipelines for latency, relevance, and cost efficiency at scale. • Uphold a culture of high efficiency, creativity, and quality.

• Build systems that turn messy, high-volume data into reliable outputs • Design APIs, own data workflows, and push performance at scale • Ship fast, debug hard problems, and care about correctness • Mentor engineers and raise the bar on code quality • Own major parts of the backend, improving performance and reliability

• Design and implement core backend services - including data modeling, compliance logic, and internal platforms that support tax automation at scale. • Build scalable systems to monitor, calculate, and apply transaction taxes across a wide range of jurisdictions and industries. • Develop and maintain our domain model for tax rules, jurisdictions, thresholds, and impositions. • Build automation pipelines for filings, payments, and customer workflows. • Use browser automation, scripting, and task queues to reduce manual work across compliance processes. • Leverage LLMs and programmatic tools to enhance tax research, rule extraction, and error handling. • Collaborate across engineering, tax, and product teams to turn complex policy into scalable software systems.

• Cross-functional Collaboration: You will join a product squad and work closely with designers, product managers, and experienced engineers across backend, frontend, mobile, and AI. • Shift in Software Engineering: Driven by AI, the role is moving toward end-to-end ownership—focusing on understanding user problems, shaping product decisions, rapid prototyping, and validating ideas, rather than just coding from strict specs. • A Shared Transition: The company is undergoing this transformation itself; you aren't expected to have everything figured out from day one. • Key Traits Valued: What matters most is your curiosity, adaptability, strong engineering judgment, and a genuine willingness to learn new ways of working. • Growth and Support: You will receive the tools, practices, and team environment needed to evolve into a product-minded, AI-enabled engineer while continuing to deepen your technical expertise.